During the past 12 months, we have used NCS-A data to investigate several important research questions that may impact nosology, clinical practice, and intervention strategies. We examined the clinical correlates of disruptive mood dysregulation disorder (DMDD) and found that this diagnosis is present among only a small group of adolescents, who often have other psychiatric and neurologic conditions (Althoff et al, 2016). We also investigated correlates of overweight/obesity (OW/OB) among adolescents with bipolar disorder (BPD), depression, and no mood disorder and found among those with BPD, adolescents with OW/OB were more likely to report suicide attempts, physical or sexual abuse, binge eating or bulimia, and comorbid conduct disorder (Goldstein et al, 2016). We are also interested in the relationship between sleep patterns and mental health in adolescents and found that youth with suboptimal sleep patterns had higher odds of an array of mental disorders and other health related outcomes. Our findings suggest that interventions to optimize sleep patterns may also benefit adolescent mental health (Zhang et al, 2017). Finally, in a study investigating the generalizability of clinical trials results for adolescent major depressive disorder (MDD), findings indicated that trials of pharmacological, and to a lesser extent, psychotherapeutic interventions, likely exclude most adolescents with MDD and consideration should be given to balancing eligibility criteria and internal validity with applicability routine clinical care, while ensuring patient safety (Blanco et al, in press). In collaboration with colleagues at Columbia University, Johns Hopkins University, and other institutes at the National Institutes of Health (NIH), we completed a study assessing the order of onset between mania and other mental disorders in U.S. adults using data from NESARC. We found that those with mania at Wave 1 had increased risk of both depression and anxiety disorders at Wave 2, while those with depression at Wave 1 had increased risk of both mania and anxiety at Wave 2. These results challenge the traditional coupling of mania and depression and indicate that further research into the links between mania and anxiety is needed (Olfson et al, 2017). In collaboration with our colleagues in Zurich, we published an analysis of the trajectory of mental disorder risk across ages 20 to 50 (Paksarian et al, 2016). We found that trajectories differed between men and women and that while very few people had persistent mental disorder across the entire age period studied, one trajectory that was consistently identified indicated high risk from the late 20s until the early 40s. In addition, we examined patterns of change in age-of-onset reports among study participants over almost 30 years of study participation. Our findings indicated that there is substantial variability in age-of-onset reports, that reports increase systematically with age, and that there may be variability according to disorder type and clinical correlates (Paksarian et al, 2017). With researchers at UPENN, we evaluated clinical patterns and predictors of symptom persistence with various psychosis spectrum trajectories and outcomes using the PNC data. Our findings of varying courses of psychosis spectrum symptoms in U.S. youth confirm those of earlier studies, and highlight that psychosis risk is a dynamic process in young people (Calkins et al, 2017). We have also investigated the associations between neurocognitive function with specific mood disorder subgroups and examined familial correlations in neurocognitive function. Our results indicate there were few differences in neurocognitive function except enhanced accuracy in specific domains among those with bipolar 1 disorder and MDD (Merikangas et al, 2017). We have continued to collaborate with researchers from the COLAUS study in Switzerland. We evaluated to what extent a genetic risk score (GRS) combining multiple genetic risk variants was associated with migraine prevalence, subtypes and severity and found that the GRS was associated with migraine without aura, but not with migraine with aura, suggesting a different genetic susceptibility background underlying the two types of migraine (Pisanu et al, 2017). Additionally, we found that the atypical subtype of MDD at baseline was associated with increased high-sensitivity C-reactive protein (a marker of inflammation linked to cardiovascular diseases) at follow-up, whereas inflammation was not a risk factor for subsequent depression (Glaus et al, in press). In a Viewpoint article in the Journal of the American Medical Association, we described challenges to the federal mandate for mental health statistics and lack of coordinated data on serious mental disorders. We proposed the directions of future studies in getting a comprehensive picture of the burden of mental and substance use disorder in the U.S. (Merikangas et al, 2017). In collaboration with researchers in Denmark, we completed a study that used Danish population registry data to assess whether the well-established association between urbanicity at birth with schizophrenia may be attributable to selective migration among those with greater genetic susceptibility. Our findings indicated that the association could not be attributed to genetic confounding, increasing confidence that the association is causal. This study has important implications for research on environmental risk factors in the etiology of schizophrenia (Paksarian et al, 2017). Public Health Impact: These studies provide valuable insight into the nature of mental disorders and their burden among children, adolescents, and adults across time. The NCS-A study was the first with comprehensive domains of emotional and behavior disorders in a nationally representative sample of U.S. youth, and the results have had significant public health impact. The PNC is also destined to become a high-impact project because it consists of a large, systematically obtained pediatric sample with enriched information from electronic medical records and direct interviews. Our studies of comorbidity in adolescents and youth, such as that between mental and substance use disorders or between sleep patterns and mental disorders, highlight the potential for identification of opportunities for intervention in adolescent mental health. The Zurich Cohort Study is an extremely valuable data source, as it is the longest community-based longitudinal study in which participants were enrolled at the beginning of adulthood. Lastly, our work on the COLAUS study has substantial potential for public health impact because it combines information regarding cardiovascular risk factors and mental disorders in a longitudinal study. Our recent work represents only the beginning of a research program that we hope will help to tease apart the longitudinal relationships between physical and mental health in the population. Future Plans: We plan to continue to analyze these rich data sources and plan to continue to explore other large population datasets such as the NESARC, the National Survey on Drug Use and Health, and the Center for Disease Control's Youth Risk Behavior Survey and Behavioral Risk Factor Surveillance System, both within our research group and with collaborators across NIH and at other institutions. We are currently focusing on mental disorders and other health related outcomes in relation to: 1) parenting style, 2) disparities based on race-ethnicity and immigrant status, 3) residential and school mobility, 4) peer and family social network characteristics, 5) lifestyle factors such as physical activity and sleep, 6) familial aggregation and comorbidities within families, and 7) biomarkers and health risk factors.